Integrated single-cell chromatin and transcriptomic analyses of human scalp reveal etiological insights into genetic risk for hair and skin disease

Abstract

Genome-wide association studies (GWAS) of hair and skin disease have identified many genetic variants associated with disease phenotypes, but identifying causal variants and interpreting their function requires deciphering gene-regulatory networks in disease-relevant cell types. To this end, we generated matched scRNA- and scATAC-seq profiles of human scalp biopsies, identifying diverse cell types of the hair follicle niche. By interrogating the integrated datasets across multiple levels of cellular resolution, we infer 50-100% more enhancer-gene links than prior approaches, and show that the aggregate accessibility at linked enhancers for highly-regulated genes predicts expression. We use these gene-regulatory maps to prioritize cell types, genes, and causal variants implicated in the pathobiology of androgenetic alopecia (AGA), eczema, and other complex traits. AGA GWAS signals are strongly and specifically enriched in dermal papilla cell open chromatin regions, supporting the role of these cells as key drivers of AGA pathogenesis. Finally, we trained machine-learning models to nominate SNPs that affect gene expression through disruption of specific transcription factor binding motifs, identifying candidate functional SNPs linked to expression of WNT10A in AGA and IL18RAP in eczema. Together, this work reveals principles of gene regulation and identifies gene regulatory consequences of natural genetic variation in complex skin and hair diseases.